Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Concept Data Analysis: Theory and Applications
Concept Data Analysis: Theory and Applications
Delivering adaptivity through context-awareness
Journal of Network and Computer Applications
Advanced inference in situation-aware computing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A survey of context modelling and reasoning techniques
Pervasive and Mobile Computing
Symbol recognition using a concept lattice of graphical patterns
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
Human activity recognition from accelerometer data using a wearable device
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
Representation and recognition of situations in sensor networks
IEEE Communications Magazine
A context management architecture for large-scale smart environments
IEEE Communications Magazine
Building health persona from personal data streams
Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia
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A variety of sensors are available nowadays for fine grain continuous monitoring of our environments in many desired ways. Comprehension of streams of data from deployed sensors in a meaningful way is critical to usability of the sensors. One such comprehension is context and situation which may affect our actions and decisions. Context is deduced from the sensor data using probabilistic methods like maximum likelihood estimation and Bayesian probabilities. Possible situations are abstracted using deduced contexts. Event trees, template and rule based methods have been used for deriving situations from contexts. Lattices are constructed using formal concept analysis methods for representation and recognition of situations. When the context information is either noisy or incomplete, set of Implication and Association Rules are derived from the lattice and used for situation recognition. For illustration, Situation of an elderly person living alone in a house, deployed with various sensors is recognized using the above technique.